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Genkit MCP

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by firebase
genkit_test.go3.93 kB
// Copyright 2025 Google LLC // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. // // SPDX-License-Identifier: Apache-2.0 package pinecone import ( "context" "strings" "testing" "github.com/firebase/genkit/go/ai" "github.com/firebase/genkit/go/core" "github.com/firebase/genkit/go/genkit" "github.com/firebase/genkit/go/internal/fakeembedder" ) func TestGenkit(t *testing.T) { if *testAPIKey == "" { t.Skip("skipping test because -test-pinecone-api-key flag not used") } if *testIndex == "" { t.Skip("skipping test because -test-pinecone-index flag not used") } // We use a different namespace for each test to avoid confusion. namespace := *testNamespace + "TestGenkit" ctx := context.Background() g := genkit.Init(context.Background(), genkit.WithPlugins(&Pinecone{APIKey: *testAPIKey})) // Get information about the index. client, err := newClient(ctx, *testAPIKey) if err != nil { t.Fatal(err) } indexData, err := client.indexData(ctx, *testIndex) if err != nil { t.Fatal(err) } dim := indexData.Dimension // Make two very similar vectors and one different vector. // Arrange for a fake embedder to return those vector // when provided with documents. v1 := make([]float32, dim) v2 := make([]float32, dim) v3 := make([]float32, dim) for i := range v1 { v1[i] = float32(i) v2[i] = float32(i) v3[i] = float32(dim - i) } v2[0] = 1 d1 := ai.DocumentFromText("hello1", nil) d2 := ai.DocumentFromText("hello2", nil) d3 := ai.DocumentFromText("goodbye", nil) embedder := fakeembedder.New() embedder.Register(d1, v1) embedder.Register(d2, v2) embedder.Register(d3, v3) emdOpts := &ai.EmbedderOptions{ Dimensions: 768, Label: "", Supports: &ai.EmbedderSupports{ Input: []string{"text"}, }, ConfigSchema: nil, } cfg := Config{ IndexID: *testIndex, Embedder: genkit.DefineEmbedder(g, "fake/embedder3", emdOpts, embedder.Embed), } retOpts := &ai.RetrieverOptions{ ConfigSchema: core.InferSchemaMap(PineconeRetrieverOptions{}), Label: "embedder3", Supports: &ai.RetrieverSupports{ Media: false, }, } ds, retriever, err := DefineRetriever(ctx, g, cfg, retOpts) if err != nil { t.Fatal(err) } t.Logf("index flag = %q, indexData.Host = %q", *testIndex, indexData.Host) err = Index(ctx, []*ai.Document{d1, d2, d3}, ds, "") if err != nil { t.Fatalf("Index operation failed: %v", err) } defer func() { idx, err := client.index(ctx, indexData.Host) if err != nil { t.Fatal(err) } var ids []string addID := func(d *ai.Document) { id, err := docID(d) if err != nil { t.Error("can't get document ID") return } ids = append(ids, id) } addID(d1) addID(d2) addID(d3) if err := idx.deleteByID(ctx, ids, namespace); err != nil { t.Errorf("error deleting test vectors: %v", err) } }() retrieverOptions := &PineconeRetrieverOptions{ K: 2, Namespace: namespace, } retrieverResp, err := genkit.Retrieve(ctx, g, ai.WithRetriever(retriever), ai.WithDocs(d1), ai.WithConfig(retrieverOptions)) if err != nil { t.Fatalf("Retrieve operation failed: %v", err) } docs := retrieverResp.Documents if len(docs) != 2 { t.Errorf("got %d results, expected 2", len(docs)) } for _, d := range docs { text := d.Content[0].Text if !strings.HasPrefix(text, "hello") { t.Errorf("returned doc text %q does not start with %q", text, "hello") } } }

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